On the seasonal variability of raindrop size distribution and associated variations in reflectivity – Rainrate relations at Tirupati, a tropical station

Sulochana, Y.; Rao, T. Narayana; Sunilkumar, K.; Chandrika, Pitta Venkata; Raman, M. Roja; Rao, S. Vijaya Bhaskara

doi:10.1016/j.jastp.2016.07.011

Cited by 15 publications

(12 citation statements)

References 45 publications

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“…Variability of DSDs in different forms of precipitation impact the radar reflectivity-rainfall intensity relationships (Z-R relationships, normally in the form of power function Z = aR b , in which a and b are parameters derived from data fitting) [12,13], and the quantitative estimation of rainfall intensity (R) by Z-R relationships can be further modified. Sulochana et al [14] investigated the Z-R relationships over a tropical station and concluded that the prefactor of Z-R relationships is larger for stratiform rain than for convective rain, which was in agreement with the results reported from two other tropical stations. Sulochana et al also found that there were large variations in Z-R relationships in different seasons.…”

Section: Introductionsupporting

confidence: 76%

“…In this study, in order to analyze the characteristics of raindrop spectra in different precipitation types, the precipitation data is classified into convective and stratiform rain based on the rainfall intensity [14]. Quality control is carried out in this study because there are errors in the measurement of large diameters of raindrops using the disdrometer.…”

Section: Precipitation Types and Quality Control (Qc)mentioning

confidence: 99%

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Seasonal Characteristics of Disdrometer-Observed Raindrop Size Distributions and Their Applications on Radar Calibration and Erosion Mechanism in a Semi-Arid Area of China

Xie

Yang

et al. 2020

Remote Sensing

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Raindrop size distributions (DSDs) are the microphysical characteristics of raindrop spectra. Rainfall characterization is important to: (1) provide information on extreme rate, thus, it has an impact on rainfall related hazard; (2) provide data for indirect observation, model and forecast; (3) calibrate and validate the parameters in radar reflectivity-rainfall intensity (Z-R) relationships (quantitative estimate precipitation, QPE) and the mechanism of precipitation erosivity. In this study, the one-year datasets of raindrop spectra were measured by an OTT Parsivel-2 Disdrometer placed in Yulin, Shaanxi Province, China. At the same time, four TE525MM Gauges were also used in the same location to check the disdrometer-measured rainfall data. The theoretical formula of raindrop kinetic energy-rainfall intensity (KE-R) relationships was derived based on the DSDs to characterize the impact of precipitation characteristics and environmental conditions on KE-R relationships in semi-arid areas. In addition, seasonal rainfall intensity curves observed by the disdrometer of the area with application to erosion were characterized and estimated. The results showed that after quality control (QC), the frequencies of raindrop spectra data in different seasons varied, and rainfalls with R within 0.5–5 mm/h accounted for the largest proportion of rainfalls in each season. The parameters in Z-R relationships (Z = aRb) were different for rainfall events of different seasons (a varies from 78.3–119.0, and b from 1.8–2.1), and the calculated KE-R relationships satisfied the form of power function KE = ARm, in which A and m are parameters derived from rainfall shape factor μ. The sensitivity analysis of parameter A with μ demonstrated the applicability of the KE-R formula to different precipitation processes in the Yulin area.

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Section: Introductionsupporting

confidence: 76%

Section: Precipitation Types and Quality Control (Qc)mentioning

confidence: 99%

Seasonal Characteristics of Disdrometer-Observed Raindrop Size Distributions and Their Applications on Radar Calibration and Erosion Mechanism in a Semi-Arid Area of China

Xie

Yang

et al. 2020

Remote Sensing

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“…No attempt was made to select individual rain events or worry about events that span midnight. The data published in Sulochana et al (2016) represents seasonal averages, which involves several months of data for each A-b pair plotted. One minute intervals would show more detail and would likely not require the dual sum used to define Model III.…”

Section: Discussionmentioning

confidence: 99%

“…Composite of Fig. 5d overlaid with A-b derived results from disdrometer data with grey symbols representing stratiform rain, red symbols for convective rain with A > 300, and green symbols for convective rain with A < 300: (a) data from Athalassa, Cyprus; (b) data from Sulochana et al (2016).…”

Section: Model Imentioning

confidence: 99%

A phenomenological relationship between vertical air motion and disdrometer derived A - b coefficients

Lane

Kasparis

Michaelides

et al. 2018

Atmospheric Research

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Using the well-known Z-R power law, Z = A R b , A-b parameters derived from a single disdrometer are readily found and can provide useful information to study rainfall drop size distributions (DSDs). However, large variations in values are often seen when comparing A-b sets from various researchers. Values of b typically range from 1.25 to 1.55 for both stratiform and convective events. The values of A approximately fall into three groups: 150 to 200 for convective, 200 to 400 for stratiform, and 400 to 500 for convective. Computing the A-b parameters using the gamma DSD, coupled with a modified drop terminal velocity model,is still air drop terminal velocity, and w is an estimate of vertical velocity of the air well above the disdrometer, shows an interesting result. This model predicts three regions of A, corresponding to w < 0, w = 0, and w > 0. Additional models that incorporate a constant vertical air velocity are also investigated. A-b sets derived from a Joss Waldvogel (JW) disdrometer and DSD data acquired near Athalassa, Cyprus, using selected 24-hour data sets from 2011 to 2014, are compared to the above models. The data is separated into two main groups: stratiform events defined by rainfall rates that did not exceed 10 mm h -1 at any time during the 24-hour period, and convective events defined by rainfall rates not flagged as stratiform. The convective rainfall is further separated into two groups: A-b pairs that fall to the left of the stratiform pairs and pairs that fall to the right. This procedure is repeated with data from other researchers that corresponds to seasonal averages. In all cases, the three vertical groupings of the A-b parameter plot seem to correlate to DSD simulations where various values of positive and negative vertical velocities are used.

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“…In India, many rain DSD studies have been conducted in southeast India, where rainfall commonly occurs with both the northeast and southwest monsoons [9,[13][14][15][16][17][18][19][20][21], and studied the difference between northeast and southwest monsoons. Recently, cloud microphysics have been extensively studied over the Western Ghats in the west coast of the Indian subcontinent, which is one of the heaviest orographic rainfall areas in India [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Orographic Rain Drop-Size Distribution at Cherrapunji, Northeast India

et al. 2020

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The rain drop size distribution (DSD) at Cherrapunji, Northeast India was observed by a laser optical disdrometer Parsivel 2 from May to October 2017; this town is known for the world’s heaviest orographic rainfall recorded. The disdrometer showed a 30% underestimation of the rainfall amount, compared with a collocated rain gauge. The observed DSD had a number of drops with a mean normalized intercept log 10 N w > 4.0 for all rain rate categories, ranging from <5 to >80 mm h − 1 , comparable to tropical oceanic DSDs. These results differ from those of tropical oceanic DSDs, in that data with a larger N w were confined to the stratiform side of a stratiform/convective separation line proposed by Bringi et al. (2009). A large number of small drops is important for quantitative precipitation estimates by in-situ radar and satellites, because it tends to miss or underestimate precipitation amounts. The large number of small drops, as defined by the second principal component (>+1.5) while using the principal component analysis approach of Dolan et al. (2018), was rare for the pre-monsoon season, but was prevalent during the monsoon season, accounting for 16% (19%) of the accumulated rainfall (precipitation period); it tended to appear over weak active spells or the beginning of active spells of intraseasonal variation during the monsoon season.

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On the seasonal variability of raindrop size distribution and associated variations in reflectivity – Rainrate relations at Tirupati, a tropical station

Cited by 15 publications

References 45 publications

Seasonal Characteristics of Disdrometer-Observed Raindrop Size Distributions and Their Applications on Radar Calibration and Erosion Mechanism in a Semi-Arid Area of China

Seasonal Characteristics of Disdrometer-Observed Raindrop Size Distributions and Their Applications on Radar Calibration and Erosion Mechanism in a Semi-Arid Area of China

A phenomenological relationship between vertical air motion and disdrometer derived A - b coefficients

Characteristics of Orographic Rain Drop-Size Distribution at Cherrapunji, Northeast India

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